This paper aims to model the joint dynamics of cryptocurrencies in a nonstationary setting. In particular, we analyze the role of cointegration relationships within a large system of cryptocurrencies in a vector error correction model (VECM) framework. To enable analysis in a dynamic setting, we...

Tail risk protection is in the focus of the financial industry and requires solid mathematical and statistical tools, especially when a trading strategy is derived. Recent hype driven by machine learning (ML) mechanisms has raised the necessity to display and understand the functionality of ML...

We develop a uniform test for detecting and dating explosive behavior of a strictly stationary GARCH(r, s) (generalized autoregressive conditional heteroskedasticity) process. Namely, we test the null hypothesis of a globally stable GARCH process with constant parameters against an alternative...

For multiple change-points detection of high-dimensional time series, we provide asymptotic theory concerning the consistency and the asymptotic distribution of the breakpoint statistics and estimated break sizes. The theory backs up a simple two- step procedure for detecting and estimating...

Modelling dynamic conditional heteroscedasticity is the daily routine in time series econometrics. We propose a weighted conditional moment estimation to potentially improve the eciency of the QMLE (quasi maximum likelihood estimation). The weights of conditional moments are selected based on...

Estimating spot covariance is an important issue to study, especially with the increasing availability of high-frequency nancial data. We study the estimation of spot covariance using a kernel method for high-frequency data. In particular, we consider rst the kernel weighted version of realized...

Strategic planning in a corporate environment is often based on experience and intuition, although internal data is usually available and can be a valuable source of information. Predicting merger & acquisition (M&A) events is at the heart of strategic management, yet not sufficiently motivated...

We investigate the relationship between underlying blockchain mechanism of cryptocurrencies and its distributional characteristics. In addition to price, we emphasise on using actual block size and block time as the operational features of cryptos. We use distributional characteristics such as...

Cryptocurrencies are gaining momentum in investor attention, are about to become a new asset class, and may provide a hedging alternative against the risk of devaluation of fiat currencies following the COVID-19 crisis. In order to provide a thorough understanding of this new asset class, risk...

Driven by increased complexity of dynamical systems, the solution of system of differential equations through numerical simulation in optimization problems has become computationally expensive. This paper provides a smart data driven mechanism to construct low dimensional surrogate models. These...